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Mammographic Image Analysis [Paperback]

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  • Category: Books (Medical)
  • Author:  Highnam, R., Brady, J.M.
  • Author:  Highnam, R., Brady, J.M.
  • ISBN-10:  9401059497
  • ISBN-10:  9401059497
  • ISBN-13:  9789401059497
  • ISBN-13:  9789401059497
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Feb-2012
  • Pub Date:  01-Feb-2012
  • SKU:  9401059497-11-SPRI
  • SKU:  9401059497-11-SPRI
  • Item ID: 100976782
  • List Price: $54.99
  • Seller: ShopSpell
  • Ships in: 5 business days
  • Transit time: Up to 5 business days
  • Delivery by: Dec 03 to Dec 05
  • Notes: Brand New Book. Order Now.

Breast cancer is a major health problem in the Western world, where it is the most common cancer among women. Approximately 1 in 12 women will develop breast cancer during the course of their lives. Over the past twenty years there have been a series of major advances in the manage? ment of women with breast cancer, ranging from novel chemotherapy and radiotherapy treatments to conservative surgery. The next twenty years are likely to see computerized image analysis playing an increasingly important role in patient management. As applications of image analysis go, medical applications are tough in general, and breast cancer image analysis is one of the toughest. There are many reasons for this: highly variable and irregular shapes of the objects of interest, changing imaging conditions, and the densely textured nature of the images. Add to this the increasing need for quantitative informa? tion, precision, and reliability (very few false positives), and the image pro? cessing challenge becomes quite daunting, in fact it pushes image analysis techniques right to their limits.Breast cancer is a major health problem in the Western world, where it is the most common cancer among women. Approximately 1 in 12 women will develop breast cancer during the course of their lives. Over the past twenty years there have been a series of major advances in the manage? ment of women with breast cancer, ranging from novel chemotherapy and radiotherapy treatments to conservative surgery. The next twenty years are likely to see computerized image analysis playing an increasingly important role in patient management. As applications of image analysis go, medical applications are tough in general, and breast cancer image analysis is one of the toughest. There are many reasons for this: highly variable and irregular shapes of the objects of interest, changing imaging conditions, and the densely textured nature of the images. Add to this the increasing need for quantitative informa? tion, l£3

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